Senior Gen AI Engineer

Weekday (YC W21)

. Design, develop, and maintain scalable data engineering and analytics solutions .

Posted 10/2/2026full-timeRemote • IndiaSenior💰 ₹1,000,000 - ₹6,500,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and developing scalable data pipelines and data processing solutions using Databricks and cloud technologies. Proficient in data engineering concepts, data modeling, and optimizing workflows for performance and scalability.

Highest-signal resume keywords

Data EngineeringDatabricksCloud-Based Data PlatformsPython ProgrammingETL/ELT

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data Pipeline DevelopmentData Processing SolutionsData ModelingDistributed Data ProcessingData QualityPerformance OptimizationAnalytics EngineeringMachine Learning SupportRelational DatabasesNon-Relational Databases

Soft Skills

Analytical SkillsProblem-Solving SkillsCommunication SkillsCollaborationProject Management

Tools & Technologies

AWSAzureGCPDatabricksAgile Methodologies

Industry Keywords

Data EngineeringAnalyticsData PlatformsAI-Driven ApplicationsData Governance

Tech Stack

Tools & technologies

AWSAzureCloudETLGoogle Cloud PlatformJavaPythonScalaSQL

About the role

Key responsibilities & impact

Design, develop, and maintain scalable data engineering and analytics solutions
Build reliable data pipelines for batch and real-time processing
Develop data platforms and workflows using Databricks and modern cloud technologies
Work with large and complex datasets for analytics, reporting, and AI-driven applications
Design data models and optimise processing workflows for performance and scalability
Integrate structured and unstructured data sources
Implement data quality, validation, monitoring, and governance practices
Collaborate with data scientists, analysts, engineers, product teams, and business stakeholders
Translate business requirements into scalable technical and data solutions
Troubleshoot pipeline, processing, performance, and integration issues
Optimise data architectures and workflows for reliability, efficiency, and cost
Contribute to cloud-based data architecture and platform modernisation
Develop reusable frameworks, components, and data engineering best practices
Support deployment, monitoring, and maintenance of production data solutions
Stay current with emerging data engineering, cloud, analytics, AI, and modern data platform technologies

Requirements

What you’ll need

5+ years of professional experience in data engineering, analytics engineering, data platforms, or a related technology role
Strong experience designing and developing scalable data pipelines and data processing solutions
Hands-on experience with Databricks and modern cloud-based data platforms
Strong understanding of data engineering concepts, data modelling, ETL/ELT, and distributed data processing
Experience with AWS, Azure, or GCP
Strong programming and scripting skills in Python, SQL, Scala, or Java
Experience with relational and non-relational databases and large-scale datasets
Understanding of data architecture, integration patterns, performance optimisation, and data quality
Experience supporting analytics, business intelligence, machine learning, or AI-driven use cases
Strong analytical and problem-solving skills
Ability to work effectively with cross-functional and technical teams
Strong communication skills for explaining technical concepts to business stakeholders
Experience working in agile, fast-paced technology environments
Ability to independently drive projects from requirements through implementation and production
Passion for learning and experimenting with emerging data, cloud, analytics, and AI technologies